Advances in mobile communications and computing have made it possible for people to communicate from almost any kind of milieu, including meeting rooms and public places. This capability brings with it a concern that communications intended to be private will be seen or overheard by outside parties. For this reason, emerging efforts to augment presence services (the services that tell instant-messaging users which other instant-messaging users are currently online and willing to receive instant messages) include ways to specify whether the parties to a would-be communication are in environments appropriate for a private communication. The Internet Engineering Task Force (IETF) proposal RFC 4480 for “RPID: Rich Presence Extensions to the Presence Information Data Format,” by H. Schulzrinne, Columbia University, V. Gurbani, Lucent, P. Kyzivat and J. Rosenberg, Cisco, June 2006 envisions presence data including a privacy attribute indicating “whether the communication service is likely to be observable by other parties;” separate values can be specified for audio, video, and text communications. A standardization of a format for representing expected levels of privacy is a step towards securing private communications, but it does not specify how the privacy information is to be collected.
In RFC 2778, “A Model for Presence and Instant Messaging,” by M. Day, Lotus, J. Rosenberg, dynamicsoft, and H. Sugano, Fujitsu, February 2000, the IETF defines “presentity” as an entity that “provides presence information to a presence service.” The proposed Parlay X presence specification includes a description of presence information: “a set of attributes that characterize the presentity, such as current activity, environment, communication means, and contact addresses.” While these efforts address mechanisms for conveying privacy-related presence information, they do not address the problem of how such information is to be gathered. One possible approach is for individuals to manually report their own evaluations of their current environments, but this can be an unwelcome distraction to an individual who is already multitasking, and does not preclude an eavesdropper sneaking up on someone engaged in a conversation. Another approach is to use location information from other users of a service (for example, E911 information from other subscribers to a cellular phone network, Wi-Fi-based location information from other users of a wireless LAN, or location information gathered from badges about their wearers' locations) to determine that those individuals are nearby. However, such an approach detects the presence only of those individuals who are participating in an activity that discloses their locations to the presence infrastructure; it does not address the problem of surreptitious eavesdropping.
Therefore, there is a need for an improved system that provides dynamic presence information, overcoming the shortcomings of the prior art.